1,720,954 research outputs found
Solving Markov decision processes via state space decomposition and time aggregation
No full textAlthough there are techniques to address large scale Markov decision processes (MDP), a computationally adequate solution of the so-called curse of dimensionality still eludes, in many aspects, a satisfactory treatment. In this paper, we advance in this issue by introducing a novel multi-subset partitioning scheme to allow for a distributed evaluation of the MDP, aiming to accelerating convergence and enable distributed policy improvement across the state space,whereby the value function and the policy improvement step can be performed independently, one subset at a time. The scheme’s innovation hinges on a design that induces communication properties that allow us to evaluate timeaggregated trajectories via absorption analysis, thereby limiting the computational effort. The paper introduces and proves the convergence of a class of distributed time aggregation algorithms that combine the partitioning scheme with two-phase time aggregation to distribute the computations and accelerate convergence. In addition, we make use of Foster’s sufficient conditions for stochastic stability to develop a new theoretical result which underpins a partition design that guarantees that large regions of the state space are rarely visited and have a marginal effect on the system’sperformance. This enables the design of approximate algorithms to find near-optimal solutions to large scale systems by focusing on the most visited regions of the state space. We validate the approach in a series of experiments featuringproduction and inventory and queuing applications. The results highlight the potential of the proposed algorithms to rapidly approach the optimal solution under different problem settings
A Novel Stochastic Epidemic Model with Application to COVID-19
Full text linkIn this paper we propose a novel SEIR stochastic epidemic model. A
distinguishing feature of this new model is that it allows us to consider a set
up under general latency and infectious period distributions. To some extent,
queuing systems with infinitely many servers and a Markov chain with
time-varying transition rate are the very technical underpinning of the paper.
Although more general, the Markov chain is as tractable as previous models for
exponentially distributed latency and infection periods. It is also
significantly simpler and more tractable than semi-Markov models with a similar
level of generality. Based on the notion of stochastic stability, we derive a
sufficient condition for a shrinking epidemic in terms of the queuing system's
occupation rate that drives the dynamics. Relying on this condition, we propose
a class of ad-hoc stabilising mitigation strategies that seek to keep a
balanced occupation rate after a prescribed mitigation-free period. We validate
the approach in the light of recent data on the COVID-19 epidemic and assess
the effect of different stabilising strategies. The results suggest that it is
possible to curb the epidemic with various occupation rate levels, as long as
the mitigation is not excessively procrastinated
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
- …
